Assesses formaldehyde levels in milk and cosmetics, indicating smartphone detection is accurate and effective.
High Resolution Image Download MS PowerPoint Slide This study reports the development of a low-cost direct method for determining formaldehyde in milk and cosmetic samples. Formaldehyde was extracted from the samples using a 3D-printed gas-diffusion microextraction module, and detection was performed with a smartphone coupled to the module for colorimetric analysis. An algorithm was created in MATLAB to automate data processing. Formaldehyde was extracted from milk by acidifying the solution and exploiting the salting-out effect. Analytical curves for different types of milk (whole, skim, semiskim, lactose-free, and ultrahigh-temperature-processed) were generated using smartphone-based detection and compared with those obtained using a traditional UV/Vis spectrophotometer. A cosmetic sample used in this research was a straightening hair cream, quantified using the standard addition calibration method. The formaldehyde concentration in the straightening hair cream was determined from smartphone images to be 0.149% (w/w), whereas the spectrophotometric method yielded 0.144% (w/w). To evaluate the method’s accuracy, a headspace gas chromatography–mass spectrometry (HS-GC-MS) method was developed and applied to quantify the samples using the standard addition method. The accuracy of the proposed method exceeded 90% when compared with digital image data obtained using chromatographic and spectrophotometric methods.
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Pinho et al. (2026) studied this question.
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